We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks at nonzero chemical potential. After integrating out the gauge fields at infinite coupling, the partition function can be written as a full contraction of a tensor network consisting of coupled local numeric and Grassmann tensors. To evaluate the partition function and to compute observables, we develop a Grassmann higher-order tensor renormalization group method, specifically tailored for this model. During the coarsening procedure, the blocking of adjacent Grassmann tensors is performed analytically, and the total number of Grassmann variables in the tensor network is reduced by a factor of two at each coarsening step. The coarse-site numeri...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
A renormalization group flow of Hamiltonians for two-dimensional classical partition functions is co...
Recently, the tensor network description with bond weights on its edges has been proposed as a novel...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We present a new tensor network algorithm for calculating the partition function of interacting quan...
We make a detailed analysis of the spontaneous Z2-symmetry breaking in the two dimensional real ϕ4 t...
Tensor networks are a class of methods for studying many-body systems. They give a geometrical descr...
We discuss the successes and limitations of statistical sampling for a sequence of models studied in...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
A renormalization group flow of Hamiltonians for two-dimensional classical partition functions is co...
Recently, the tensor network description with bond weights on its edges has been proposed as a novel...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We present a new tensor network algorithm for calculating the partition function of interacting quan...
We make a detailed analysis of the spontaneous Z2-symmetry breaking in the two dimensional real ϕ4 t...
Tensor networks are a class of methods for studying many-body systems. They give a geometrical descr...
We discuss the successes and limitations of statistical sampling for a sequence of models studied in...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
A renormalization group flow of Hamiltonians for two-dimensional classical partition functions is co...
Recently, the tensor network description with bond weights on its edges has been proposed as a novel...